A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors

A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors

Abstract In recent years, machine learning has gained substantial attention for its ability to predict complex chemical and biological properties, including those of pharmaceutical compounds. This study proposes a machine learning-based quantitative structure-property relationship (QSPR) model for p...

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Detalles Bibliográficos
Autores principales: Huiling Qin, Mudassar Rehman, Muhammad Farhan Hanif, Muhammad Yousaf Bhatti, Muhammad Kamran Siddiqui, Mohamed Abubakar Fiidow
Formato: Artículo
Lenguaje:English
Publicado: Nature Portfolio 2025-01-01
Colección:Scientific Reports
Materias:
Anti-arrhythmia drugs
Linear regression model
Pyhton algorithm
Topological indices
Entropy
QSPR analysis
Acceso en línea:https://doi.org/10.1038/s41598-025-85352-0

Internet

https://doi.org/10.1038/s41598-025-85352-0

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